Chenglei Si

607 total citations
13 papers, 159 citations indexed

About

Chenglei Si is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Sociology and Political Science. According to data from OpenAlex, Chenglei Si has authored 13 papers receiving a total of 159 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 1 paper in Sociology and Political Science. Recurrent topics in Chenglei Si's work include Topic Modeling (11 papers), Natural Language Processing Techniques (9 papers) and Multimodal Machine Learning Applications (3 papers). Chenglei Si is often cited by papers focused on Topic Modeling (11 papers), Natural Language Processing Techniques (9 papers) and Multimodal Machine Learning Applications (3 papers). Chenglei Si collaborates with scholars based in United States, China and Sweden. Chenglei Si's co-authors include Shijin Wang, Yiming Cui, Guoping Hu, Ting Liu, Wentao Ma, Jordan Boyd‐Graber, Yasheng Wang, Min‐Yen Kan, Zhengyan Zhang and Maosong Sun and has published in prestigious journals such as Transactions of the Association for Computational Linguistics, National University of Singapore and arXiv (Cornell University).

In The Last Decade

Chenglei Si

13 papers receiving 154 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Chenglei Si United States	8	131	25	22	12	7	13	159
Or Honovich Israel	7	199 1.5×	40 1.6×	29 1.3×	6 0.5×	6 0.9×	10	221
Mohsen Mesgar Germany	6	182 1.4×	11 0.4×	26 1.2×	12 1.0×	9 1.3×	16	194
Kenton Murray United States	7	115 0.9×	34 1.4×	37 1.7×	5 0.4×	7 1.0×	19	139
Qinghong Han China	4	152 1.2×	24 1.0×	17 0.8×	4 0.3×	9 1.3×	4	171
Iulia Turc United States	4	139 1.1×	35 1.4×	21 1.0×	9 0.8×	9 1.3×	5	158
Jon Saad-Falcon United States	4	127 1.0×	52 2.1×	35 1.6×	7 0.6×	4 0.6×	9	170
Yaowei Zheng China	5	125 1.0×	26 1.0×	20 0.9×	8 0.7×	5 0.7×	7	160
Sho Takase Japan	10	286 2.2×	52 2.1×	29 1.3×	6 0.5×	12 1.7×	31	316
Matthias Gallé France	6	117 0.9×	31 1.2×	15 0.7×	7 0.6×	14 2.0×	25	147

Countries citing papers authored by Chenglei Si

Since Specialization

Citations

This map shows the geographic impact of Chenglei Si's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chenglei Si with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chenglei Si more than expected).

Fields of papers citing papers by Chenglei Si

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chenglei Si. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chenglei Si. The network helps show where Chenglei Si may publish in the future.

Co-authorship network of co-authors of Chenglei Si

This figure shows the co-authorship network connecting the top 25 collaborators of Chenglei Si. A scholar is included among the top collaborators of Chenglei Si based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chenglei Si. Chenglei Si is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

Si, Chenglei, et al.. (2024). Large Language Models Help Humans Verify Truthfulness – Except When They Are Convincingly Wrong. 1459–1474. 6 indexed citations

Si, Chenglei, et al.. (2023). Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations. 11289–11310. 2 indexed citations

Si, Chenglei, et al.. (2023). Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs Through a Global Prompt Hacking Competition. UA Campus Repository (The University of Arizona). 4945–4977. 12 indexed citations

Si, Chenglei, Zhengyan Zhang, Fanchao Qi, et al.. (2023). Sub-Character Tokenization for Chinese Pretrained Language Models. Transactions of the Association for Computational Linguistics. 11. 469–487. 7 indexed citations

Si, Chenglei, et al.. (2023). READIN: A Chinese Multi-Task Benchmark with Realistic and Diverse Input Noises. 8272–8285. 1 indexed citations

Si, Chenglei, Weijia Shi, Chen Zhao, Luke Zettlemoyer, & Jordan Boyd‐Graber. (2023). Getting MoRE out of Mixture of Language Model Reasoning Experts. 8234–8249. 3 indexed citations

Si, Chenglei, Chen Zhao, Sewon Min, & Jordan Boyd‐Graber. (2022). Re-Examining Calibration: The Case of Question Answering. 2814–2829. 3 indexed citations

Si, Chenglei, Zhengyan Zhang, Fanchao Qi, et al.. (2021). Better Robustness by More Coverage: Adversarial and Mixup Data Augmentation for Robust Finetuning. 1569–1576. 34 indexed citations

Si, Chenglei, Chen Zhao, & Jordan Boyd‐Graber. (2021). What’s in a Name? Answer Equivalence For Open-Domain Question Answering. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 9623–9629. 10 indexed citations

10.

Si, Chenglei, et al.. (2021). Benchmarking Robustness of Machine Reading Comprehension Models. 634–644. 16 indexed citations

11.

Ma, Wentao, Yiming Cui, Chenglei Si, et al.. (2020). CharBERT: Character-aware Pre-trained Language Model. arXiv (Cornell University). 39–50. 45 indexed citations

12.

Si, Chenglei, Kui Wu, Ai Ti Aw, & Min‐Yen Kan. (2019). Sentiment Aware Neural Machine Translation. National University of Singapore. 200–206. 12 indexed citations

13.

Si, Chenglei, et al.. (2019). Dataset Mention Extraction and Classification. National University of Singapore. 31–36. 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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